Overview

Brought to you by YData

Dataset statistics

Number of variables40
Number of observations5906
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory801.7 KiB
Average record size in memory139.0 B

Variable types

Numeric11
Categorical2
Boolean27

Alerts

regla_duracion_pct_ok has constant value "True" Constant
estado_civil_CASADO is highly overall correlated with estado_civil_SOLTEROHigh correlation
estado_civil_SOLTERO is highly overall correlated with estado_civil_CASADOHigh correlation
estado_cliente_ACTIVO is highly overall correlated with estado_cliente_PASIVO and 2 other fieldsHigh correlation
estado_cliente_PASIVO is highly overall correlated with estado_cliente_ACTIVO and 2 other fieldsHigh correlation
falta_pago_N is highly overall correlated with estado_cliente_ACTIVO and 3 other fieldsHigh correlation
falta_pago_Y is highly overall correlated with estado_cliente_ACTIVO and 3 other fieldsHigh correlation
gastos_ult_12m is highly overall correlated with operaciones_ult_12mHigh correlation
genero_F is highly overall correlated with genero_MHigh correlation
genero_M is highly overall correlated with genero_FHigh correlation
importe_solicitado is highly overall correlated with pct_ingresoHigh correlation
operaciones_ult_12m is highly overall correlated with gastos_ult_12mHigh correlation
pct_ingreso is highly overall correlated with importe_solicitadoHigh correlation
situacion_vivienda_ALQUILER is highly overall correlated with situacion_vivienda_HIPOTECAHigh correlation
situacion_vivienda_HIPOTECA is highly overall correlated with situacion_vivienda_ALQUILERHigh correlation
tasa_interes is highly overall correlated with falta_pago_N and 1 other fieldsHigh correlation
situacion_vivienda_OTROS is highly imbalanced (96.3%) Imbalance
situacion_vivienda_PROPIA is highly imbalanced (63.4%) Imbalance
objetivo_credito_MEJORAS_HOGAR is highly imbalanced (57.6%) Imbalance
estado_civil_DESCONOCIDO is highly imbalanced (62.8%) Imbalance
estado_civil_DIVORCIADO is highly imbalanced (63.1%) Imbalance
nivel_educativo_POSGRADO_COMPLETO is highly imbalanced (73.3%) Imbalance
nivel_educativo_POSGRADO_INCOMPLETO is highly imbalanced (71.6%) Imbalance
antiguedad_empleado has 842 (14.3%) zeros Zeros
personas_a_cargo has 515 (8.7%) zeros Zeros

Reproduction

Analysis started2025-07-12 15:25:37.926970
Analysis finished2025-07-12 15:25:52.448955
Duration14.52 seconds
Software versionydata-profiling vv4.13.0
Download configurationconfig.json

Variables

edad
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.552997
Minimum20
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size92.3 KiB
2025-07-12T17:25:52.548396image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile21
Q122
median23
Q325
95-th percentile26
Maximum26
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.515481
Coefficient of variation (CV)0.064343449
Kurtosis-1.0679789
Mean23.552997
Median Absolute Deviation (MAD)1
Skewness0.10280177
Sum139104
Variance2.2966828
MonotonicityNot monotonic
2025-07-12T17:25:52.665775image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
22 1311
22.2%
23 1254
21.2%
24 1104
18.7%
25 990
16.8%
26 798
13.5%
21 446
 
7.6%
20 3
 
0.1%
ValueCountFrequency (%)
20 3
 
0.1%
21 446
 
7.6%
22 1311
22.2%
23 1254
21.2%
24 1104
18.7%
25 990
16.8%
26 798
13.5%
ValueCountFrequency (%)
26 798
13.5%
25 990
16.8%
24 1104
18.7%
23 1254
21.2%
22 1311
22.2%
21 446
 
7.6%
20 3
 
0.1%

importe_solicitado
Real number (ℝ)

High correlation 

Distinct415
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8231.0913
Minimum500
Maximum35000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size92.3 KiB
2025-07-12T17:25:52.782933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile2000
Q14500
median6600
Q310000
95-th percentile20000
Maximum35000
Range34500
Interquartile range (IQR)5500

Descriptive statistics

Standard deviation5801.701
Coefficient of variation (CV)0.70485198
Kurtosis2.3300522
Mean8231.0913
Median Absolute Deviation (MAD)2600
Skewness1.5266463
Sum48612825
Variance33659734
MonotonicityNot monotonic
2025-07-12T17:25:53.251436image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5000 455
 
7.7%
6000 439
 
7.4%
8000 336
 
5.7%
7000 269
 
4.6%
4000 248
 
4.2%
10000 218
 
3.7%
3000 200
 
3.4%
20000 175
 
3.0%
12000 154
 
2.6%
9000 151
 
2.6%
Other values (405) 3261
55.2%
ValueCountFrequency (%)
500 1
 
< 0.1%
750 1
 
< 0.1%
800 1
 
< 0.1%
900 1
 
< 0.1%
1000 81
1.4%
1050 1
 
< 0.1%
1100 1
 
< 0.1%
1200 40
0.7%
1250 1
 
< 0.1%
1275 2
 
< 0.1%
ValueCountFrequency (%)
35000 13
0.2%
34000 1
 
< 0.1%
33950 1
 
< 0.1%
33000 1
 
< 0.1%
32500 1
 
< 0.1%
31300 1
 
< 0.1%
31050 1
 
< 0.1%
30000 16
0.3%
29800 1
 
< 0.1%
29100 2
 
< 0.1%

duracion_credito
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size92.3 KiB
3
2949 
4
2948 
2
 
9

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters5906
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row4
3rd row3
4th row4
5th row3

Common Values

ValueCountFrequency (%)
3 2949
49.9%
4 2948
49.9%
2 9
 
0.2%

Length

2025-07-12T17:25:53.333976image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-07-12T17:25:53.396868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
3 2949
49.9%
4 2948
49.9%
2 9
 
0.2%

Most occurring characters

ValueCountFrequency (%)
3 2949
49.9%
4 2948
49.9%
2 9
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5906
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 2949
49.9%
4 2948
49.9%
2 9
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5906
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 2949
49.9%
4 2948
49.9%
2 9
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5906
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 2949
49.9%
4 2948
49.9%
2 9
 
0.2%

antiguedad_empleado
Real number (ℝ)

Zeros 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8924822
Minimum0
Maximum11
Zeros842
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size92.3 KiB
2025-07-12T17:25:53.446894image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q36
95-th percentile9
Maximum11
Range11
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.8392056
Coefficient of variation (CV)0.72940746
Kurtosis-0.88735972
Mean3.8924822
Median Absolute Deviation (MAD)2
Skewness0.33580519
Sum22989
Variance8.0610883
MonotonicityNot monotonic
2025-07-12T17:25:53.513382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 842
14.3%
2 773
13.1%
3 697
11.8%
5 643
10.9%
6 622
10.5%
1 617
10.4%
4 511
8.7%
7 449
7.6%
8 345
5.8%
9 244
 
4.1%
Other values (2) 163
 
2.8%
ValueCountFrequency (%)
0 842
14.3%
1 617
10.4%
2 773
13.1%
3 697
11.8%
4 511
8.7%
5 643
10.9%
6 622
10.5%
7 449
7.6%
8 345
5.8%
9 244
 
4.1%
ValueCountFrequency (%)
11 15
 
0.3%
10 148
 
2.5%
9 244
 
4.1%
8 345
5.8%
7 449
7.6%
6 622
10.5%
5 643
10.9%
4 511
8.7%
3 697
11.8%
2 773
13.1%

ingresos
Real number (ℝ)

Distinct1231
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51113.26
Minimum9600
Maximum500000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size92.3 KiB
2025-07-12T17:25:53.613615image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum9600
5-th percentile20400
Q134000
median47000
Q360000
95-th percentile98850
Maximum500000
Range490400
Interquartile range (IQR)26000

Descriptive statistics

Standard deviation29333.794
Coefficient of variation (CV)0.57389794
Kurtosis23.294515
Mean51113.26
Median Absolute Deviation (MAD)13000
Skewness3.4547132
Sum3.0187491 × 108
Variance8.604715 × 108
MonotonicityNot monotonic
2025-07-12T17:25:53.736508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60000 241
 
4.1%
30000 207
 
3.5%
50000 193
 
3.3%
40000 166
 
2.8%
45000 141
 
2.4%
65000 138
 
2.3%
48000 134
 
2.3%
36000 125
 
2.1%
55000 122
 
2.1%
42000 117
 
2.0%
Other values (1221) 4322
73.2%
ValueCountFrequency (%)
9600 1
 
< 0.1%
9840 1
 
< 0.1%
9960 1
 
< 0.1%
10000 7
0.1%
10560 1
 
< 0.1%
10668 1
 
< 0.1%
10980 1
 
< 0.1%
11000 3
0.1%
11476 1
 
< 0.1%
11520 1
 
< 0.1%
ValueCountFrequency (%)
500000 1
 
< 0.1%
306000 1
 
< 0.1%
300000 5
0.1%
287000 1
 
< 0.1%
280000 1
 
< 0.1%
277104 1
 
< 0.1%
260000 1
 
< 0.1%
250000 2
 
< 0.1%
234000 3
0.1%
230000 1
 
< 0.1%

pct_ingreso
Real number (ℝ)

High correlation 

Distinct71
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.17687437
Minimum0.01
Maximum0.83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size92.3 KiB
2025-07-12T17:25:53.848528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.04
Q10.1
median0.15
Q30.23
95-th percentile0.39
Maximum0.83
Range0.82
Interquartile range (IQR)0.13

Descriptive statistics

Standard deviation0.11112549
Coefficient of variation (CV)0.62827356
Kurtosis1.776837
Mean0.17687437
Median Absolute Deviation (MAD)0.07
Skewness1.1903152
Sum1044.62
Variance0.012348874
MonotonicityNot monotonic
2025-07-12T17:25:53.930682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1 297
 
5.0%
0.11 266
 
4.5%
0.13 264
 
4.5%
0.15 260
 
4.4%
0.08 258
 
4.4%
0.09 254
 
4.3%
0.12 241
 
4.1%
0.14 240
 
4.1%
0.07 235
 
4.0%
0.17 234
 
4.0%
Other values (61) 3357
56.8%
ValueCountFrequency (%)
0.01 11
 
0.2%
0.02 53
 
0.9%
0.03 125
2.1%
0.04 173
2.9%
0.05 184
3.1%
0.06 176
3.0%
0.07 235
4.0%
0.08 258
4.4%
0.09 254
4.3%
0.1 297
5.0%
ValueCountFrequency (%)
0.83 1
 
< 0.1%
0.77 2
< 0.1%
0.72 1
 
< 0.1%
0.71 2
< 0.1%
0.7 1
 
< 0.1%
0.69 2
< 0.1%
0.68 1
 
< 0.1%
0.67 1
 
< 0.1%
0.65 2
< 0.1%
0.64 3
0.1%

tasa_interes
Real number (ℝ)

High correlation 

Distinct290
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.993945
Minimum5.42
Maximum22.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size92.3 KiB
2025-07-12T17:25:54.036062image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum5.42
5-th percentile6.03
Q17.9
median10.99
Q313.43
95-th percentile16.32
Maximum22.11
Range16.69
Interquartile range (IQR)5.53

Descriptive statistics

Standard deviation3.2004187
Coefficient of variation (CV)0.29110739
Kurtosis-0.69880662
Mean10.993945
Median Absolute Deviation (MAD)2.5
Skewness0.20245336
Sum64930.24
Variance10.24268
MonotonicityNot monotonic
2025-07-12T17:25:54.135150image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.99 163
 
2.8%
7.51 159
 
2.7%
7.9 129
 
2.2%
7.49 126
 
2.1%
7.88 116
 
2.0%
5.42 112
 
1.9%
9.99 102
 
1.7%
11.49 93
 
1.6%
11.71 90
 
1.5%
13.49 84
 
1.4%
Other values (280) 4732
80.1%
ValueCountFrequency (%)
5.42 112
1.9%
5.79 69
1.2%
5.99 71
1.2%
6 4
 
0.1%
6.03 82
1.4%
6.17 41
 
0.7%
6.39 9
 
0.2%
6.54 55
0.9%
6.62 77
1.3%
6.76 43
 
0.7%
ValueCountFrequency (%)
22.11 1
< 0.1%
21.74 2
< 0.1%
21.27 1
< 0.1%
21.21 1
< 0.1%
20.89 1
< 0.1%
20.62 1
< 0.1%
20.25 1
< 0.1%
20.16 1
< 0.1%
20.03 2
< 0.1%
19.91 2
< 0.1%

estado_credito
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size92.3 KiB
0
4459 
1
1447 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters5906
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 4459
75.5%
1 1447
 
24.5%

Length

2025-07-12T17:25:54.214812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-07-12T17:25:54.279115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 4459
75.5%
1 1447
 
24.5%

Most occurring characters

ValueCountFrequency (%)
0 4459
75.5%
1 1447
 
24.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5906
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 4459
75.5%
1 1447
 
24.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5906
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 4459
75.5%
1 1447
 
24.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5906
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 4459
75.5%
1 1447
 
24.5%

antiguedad_cliente
Real number (ℝ)

Distinct44
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.955977
Minimum13
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size92.3 KiB
2025-07-12T17:25:54.330500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile22
Q132
median36
Q340
95-th percentile50
Maximum56
Range43
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.9664469
Coefficient of variation (CV)0.22156113
Kurtosis0.4089564
Mean35.955977
Median Absolute Deviation (MAD)4
Skewness-0.094761216
Sum212356
Variance63.464277
MonotonicityNot monotonic
2025-07-12T17:25:54.431795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
36 1421
24.1%
34 219
 
3.7%
37 203
 
3.4%
38 201
 
3.4%
31 199
 
3.4%
35 191
 
3.2%
33 188
 
3.2%
40 187
 
3.2%
39 184
 
3.1%
41 181
 
3.1%
Other values (34) 2732
46.3%
ValueCountFrequency (%)
13 39
0.7%
14 11
 
0.2%
15 19
 
0.3%
16 20
 
0.3%
17 18
 
0.3%
18 33
0.6%
19 31
0.5%
20 47
0.8%
21 48
0.8%
22 67
1.1%
ValueCountFrequency (%)
56 63
1.1%
55 20
 
0.3%
54 32
 
0.5%
53 46
0.8%
52 34
 
0.6%
51 47
0.8%
50 60
1.0%
49 88
1.5%
48 93
1.6%
47 102
1.7%

gastos_ult_12m
Real number (ℝ)

High correlation 

Distinct3711
Distinct (%)62.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4418.8666
Minimum510
Maximum18484
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size92.3 KiB
2025-07-12T17:25:54.530486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum510
5-th percentile1293
Q12153.25
median3912
Q34739
95-th percentile14256.75
Maximum18484
Range17974
Interquartile range (IQR)2585.75

Descriptive statistics

Standard deviation3418.6798
Coefficient of variation (CV)0.77365537
Kurtosis3.8839508
Mean4418.8666
Median Absolute Deviation (MAD)1310.5
Skewness2.0454448
Sum26097826
Variance11687372
MonotonicityNot monotonic
2025-07-12T17:25:54.631587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4509 7
 
0.1%
4697 7
 
0.1%
4220 7
 
0.1%
2229 7
 
0.1%
4598 7
 
0.1%
4890 6
 
0.1%
4087 6
 
0.1%
4037 6
 
0.1%
4751 6
 
0.1%
4277 6
 
0.1%
Other values (3701) 5841
98.9%
ValueCountFrequency (%)
510 1
< 0.1%
530 1
< 0.1%
569 1
< 0.1%
594 1
< 0.1%
596 1
< 0.1%
597 1
< 0.1%
615 1
< 0.1%
643 1
< 0.1%
646 1
< 0.1%
647 2
< 0.1%
ValueCountFrequency (%)
18484 1
< 0.1%
17995 1
< 0.1%
17744 1
< 0.1%
17634 1
< 0.1%
17628 1
< 0.1%
17437 1
< 0.1%
17390 1
< 0.1%
17350 1
< 0.1%
17119 1
< 0.1%
17064 1
< 0.1%

limite_credito_tc
Real number (ℝ)

Distinct4152
Distinct (%)70.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8593.3476
Minimum1438.3
Maximum34516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size92.3 KiB
2025-07-12T17:25:54.730193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1438.3
5-th percentile1438.3
Q12532.25
median4460
Q310996.25
95-th percentile34042.5
Maximum34516
Range33077.7
Interquartile range (IQR)8464

Descriptive statistics

Standard deviation9098.3814
Coefficient of variation (CV)1.0587703
Kurtosis1.809038
Mean8593.3476
Median Absolute Deviation (MAD)2549
Skewness1.6699191
Sum50752311
Variance82780543
MonotonicityNot monotonic
2025-07-12T17:25:54.828341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1438.3 310
 
5.2%
34516 291
 
4.9%
15987 9
 
0.2%
23981 9
 
0.2%
9959 8
 
0.1%
3735 6
 
0.1%
7469 6
 
0.1%
14938 5
 
0.1%
2035 5
 
0.1%
2077 5
 
0.1%
Other values (4142) 5252
88.9%
ValueCountFrequency (%)
1438.3 310
5.2%
1439 2
 
< 0.1%
1440 1
 
< 0.1%
1441 2
 
< 0.1%
1442 1
 
< 0.1%
1443 3
 
0.1%
1451 1
 
< 0.1%
1452 2
 
< 0.1%
1454 1
 
< 0.1%
1456 2
 
< 0.1%
ValueCountFrequency (%)
34516 291
4.9%
34496 1
 
< 0.1%
34427 1
 
< 0.1%
34173 1
 
< 0.1%
34162 1
 
< 0.1%
34058 1
 
< 0.1%
33996 1
 
< 0.1%
33913 1
 
< 0.1%
33905 1
 
< 0.1%
33870 1
 
< 0.1%

operaciones_ult_12m
Real number (ℝ)

High correlation 

Distinct124
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.910938
Minimum10
Maximum139
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size92.3 KiB
2025-07-12T17:25:54.913645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile28
Q145
median67
Q381
95-th percentile106
Maximum139
Range129
Interquartile range (IQR)36

Descriptive statistics

Standard deviation23.48286
Coefficient of variation (CV)0.36177047
Kurtosis-0.34175494
Mean64.910938
Median Absolute Deviation (MAD)17
Skewness0.16767074
Sum383364
Variance551.44473
MonotonicityNot monotonic
2025-07-12T17:25:55.028324image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69 129
 
2.2%
81 128
 
2.2%
77 127
 
2.2%
78 121
 
2.0%
71 117
 
2.0%
70 112
 
1.9%
82 111
 
1.9%
74 110
 
1.9%
75 109
 
1.8%
73 109
 
1.8%
Other values (114) 4733
80.1%
ValueCountFrequency (%)
10 3
 
0.1%
12 2
 
< 0.1%
13 1
 
< 0.1%
14 5
 
0.1%
15 7
0.1%
16 8
0.1%
17 9
0.2%
18 13
0.2%
19 8
0.1%
20 12
0.2%
ValueCountFrequency (%)
139 1
 
< 0.1%
138 1
 
< 0.1%
134 1
 
< 0.1%
131 5
0.1%
130 3
0.1%
129 5
0.1%
128 7
0.1%
127 5
0.1%
126 6
0.1%
125 7
0.1%

personas_a_cargo
Real number (ℝ)

Zeros 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3489672
Minimum0
Maximum5
Zeros515
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size92.3 KiB
2025-07-12T17:25:55.101689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.288507
Coefficient of variation (CV)0.54854196
Kurtosis-0.66051554
Mean2.3489672
Median Absolute Deviation (MAD)1
Skewness-0.027524224
Sum13873
Variance1.6602504
MonotonicityNot monotonic
2025-07-12T17:25:55.165074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 1613
27.3%
2 1570
26.6%
1 1059
17.9%
4 910
15.4%
0 515
 
8.7%
5 239
 
4.0%
ValueCountFrequency (%)
0 515
 
8.7%
1 1059
17.9%
2 1570
26.6%
3 1613
27.3%
4 910
15.4%
5 239
 
4.0%
ValueCountFrequency (%)
5 239
 
4.0%
4 910
15.4%
3 1613
27.3%
2 1570
26.6%
1 1059
17.9%
0 515
 
8.7%

situacion_vivienda_ALQUILER
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
True
3641 
False
2265 
ValueCountFrequency (%)
True 3641
61.6%
False 2265
38.4%
2025-07-12T17:25:55.217161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_HIPOTECA
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
4078 
True
1828 
ValueCountFrequency (%)
False 4078
69.0%
True 1828
31.0%
2025-07-12T17:25:55.250127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_OTROS
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
5883 
True
 
23
ValueCountFrequency (%)
False 5883
99.6%
True 23
 
0.4%
2025-07-12T17:25:55.282324image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_PROPIA
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
5492 
True
 
414
ValueCountFrequency (%)
False 5492
93.0%
True 414
 
7.0%
2025-07-12T17:25:55.330312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
4539 
True
1367 
ValueCountFrequency (%)
False 4539
76.9%
True 1367
 
23.1%
2025-07-12T17:25:55.363544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
4921 
True
985 
ValueCountFrequency (%)
False 4921
83.3%
True 985
 
16.7%
2025-07-12T17:25:55.398726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
5396 
True
 
510
ValueCountFrequency (%)
False 5396
91.4%
True 510
 
8.6%
2025-07-12T17:25:55.435924image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
4906 
True
1000 
ValueCountFrequency (%)
False 4906
83.1%
True 1000
 
16.9%
2025-07-12T17:25:55.478564image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
4919 
True
987 
ValueCountFrequency (%)
False 4919
83.3%
True 987
 
16.7%
2025-07-12T17:25:55.513507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
4849 
True
1057 
ValueCountFrequency (%)
False 4849
82.1%
True 1057
 
17.9%
2025-07-12T17:25:55.551922image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

falta_pago_N
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
True
4856 
False
1050 
ValueCountFrequency (%)
True 4856
82.2%
False 1050
 
17.8%
2025-07-12T17:25:55.581844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

falta_pago_Y
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
4856 
True
1050 
ValueCountFrequency (%)
False 4856
82.2%
True 1050
 
17.8%
2025-07-12T17:25:55.628351image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

regla_duracion_pct_ok
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
True
5906 
ValueCountFrequency (%)
True 5906
100.0%
2025-07-12T17:25:55.669522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_CASADO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
3164 
True
2742 
ValueCountFrequency (%)
False 3164
53.6%
True 2742
46.4%
2025-07-12T17:25:55.704665image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_DESCONOCIDO
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
5483 
True
 
423
ValueCountFrequency (%)
False 5483
92.8%
True 423
 
7.2%
2025-07-12T17:25:55.739933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_DIVORCIADO
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
5487 
True
 
419
ValueCountFrequency (%)
False 5487
92.9%
True 419
 
7.1%
2025-07-12T17:25:55.765712image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_SOLTERO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
3584 
True
2322 
ValueCountFrequency (%)
False 3584
60.7%
True 2322
39.3%
2025-07-12T17:25:55.813568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_cliente_ACTIVO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
True
4920 
False
986 
ValueCountFrequency (%)
True 4920
83.3%
False 986
 
16.7%
2025-07-12T17:25:55.851996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_cliente_PASIVO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
4920 
True
986 
ValueCountFrequency (%)
False 4920
83.3%
True 986
 
16.7%
2025-07-12T17:25:55.883903image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

genero_F
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
True
3157 
False
2749 
ValueCountFrequency (%)
True 3157
53.5%
False 2749
46.5%
2025-07-12T17:25:55.913627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

genero_M
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
3157 
True
2749 
ValueCountFrequency (%)
False 3157
53.5%
True 2749
46.5%
2025-07-12T17:25:55.981982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
5013 
True
893 
ValueCountFrequency (%)
False 5013
84.9%
True 893
 
15.1%
2025-07-12T17:25:56.015266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
5637 
True
 
269
ValueCountFrequency (%)
False 5637
95.4%
True 269
 
4.6%
2025-07-12T17:25:56.051103image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
5614 
True
 
292
ValueCountFrequency (%)
False 5614
95.1%
True 292
 
4.9%
2025-07-12T17:25:56.081903image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
4722 
True
1184 
ValueCountFrequency (%)
False 4722
80.0%
True 1184
 
20.0%
2025-07-12T17:25:56.129431image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
4147 
True
1759 
ValueCountFrequency (%)
False 4147
70.2%
True 1759
29.8%
2025-07-12T17:25:56.168571image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
False
4397 
True
1509 
ValueCountFrequency (%)
False 4397
74.4%
True 1509
 
25.6%
2025-07-12T17:25:56.204084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Interactions

2025-07-12T17:25:50.804403image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:41.092894image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:41.987084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:42.947771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:43.834538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:45.138734image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:46.038526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:46.982395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:47.898340image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:48.871395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:49.867090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:50.884208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:41.167983image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:42.077689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:43.022825image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:43.916692image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:45.218911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:46.129181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:47.056539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:47.992101image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:48.956020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:49.949054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:50.965628image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:41.255194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:42.170957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:43.106668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:43.999723image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:45.302953image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:46.217184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:47.137845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:48.084708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:49.050223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:50.036735image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:51.047333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:41.333115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:42.258138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:43.186114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:44.082555image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:45.386562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:46.297554image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:47.215755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:48.173735image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:49.137008image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:50.116804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:51.114135image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:41.416351image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:42.339634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:43.264565image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:44.157222image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:45.473179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:46.386632image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:47.290115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:48.257826image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:49.229024image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:50.201087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:51.196615image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:41.499739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:42.433738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:43.342262image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:44.236868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:45.548933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:46.470047image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:47.364222image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:48.343663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:49.325453image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:50.286996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:51.284948image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:41.581973image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:42.520259image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:43.423287image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:44.714761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:45.630314image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:46.553619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:47.443282image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:48.436588image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:49.418921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:50.363195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:51.362480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:41.655432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:42.604717image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:43.510611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:44.796750image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:45.713250image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:46.639267image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:47.515817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:48.524609image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:49.504235image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:50.455530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:51.445721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:41.746465image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:42.691794image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:43.598439image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:44.884994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:45.794994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:46.721684image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:47.602762image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:48.613863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:49.593117image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:50.537814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:51.532679image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:41.829030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:42.779000image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:43.682326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:44.972775image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:45.877819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:46.819465image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:47.688450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:48.704876image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:49.684036image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:50.635338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:51.612203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:41.913667image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:42.862126image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:43.763888image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:45.053233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:45.966038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:46.902283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:47.773668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:48.793238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:49.773858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-12T17:25:50.718515image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-07-12T17:25:56.304706image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
antiguedad_clienteantiguedad_empleadoduracion_creditoedadestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOestado_creditofalta_pago_Nfalta_pago_Ygastos_ult_12mgenero_Fgenero_Mimporte_solicitadoingresoslimite_credito_tcnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETOobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDoperaciones_ult_12mpct_ingresopersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAtasa_interes
antiguedad_cliente1.000-0.0010.0000.0050.0400.0260.0470.0590.0000.0000.0270.0450.045-0.0210.0290.0290.0370.008-0.0030.0200.0290.0180.0000.0230.0310.0000.0000.0170.0540.0370.000-0.0380.038-0.1070.0330.0450.0000.0190.000
antiguedad_empleado-0.0011.0000.0220.1170.0240.0160.0000.0210.0250.0250.1050.0290.0290.0550.0000.0000.1150.189-0.0170.0000.0290.0000.0130.0490.0220.0590.0300.0990.0150.0170.0000.048-0.013-0.0000.1990.1910.0150.036-0.064
duracion_credito0.0000.0221.0000.0000.0160.0000.0000.0130.0050.0050.0450.0000.0000.0110.0060.0060.1120.0000.0280.0080.0220.0000.0000.0120.0000.0270.0080.0130.0000.0230.0250.0070.4270.0120.0000.0000.0000.0000.036
edad0.0050.1170.0001.0000.0000.0000.0340.0150.0160.0160.0370.0000.0000.0080.0000.0000.0740.1460.0060.0000.0020.0330.0000.0000.0000.1690.0170.1930.0220.0000.0490.001-0.0360.0100.0000.0260.0250.0330.010
estado_civil_CASADO0.0400.0240.0160.0001.0000.2580.2560.7490.0310.0310.0290.0000.0000.1750.0000.0000.0870.0420.0650.0000.0000.0000.0000.0000.0030.0000.0090.0000.0000.0000.0000.1670.0500.0000.0230.0140.0110.0000.000
estado_civil_DESCONOCIDO0.0260.0160.0000.0000.2581.0000.0740.2230.0000.0000.0300.0000.0000.0350.0160.0160.0400.0430.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0210.0100.0230.0060.0070.0000.0000.034
estado_civil_DIVORCIADO0.0470.0000.0000.0340.2560.0741.0000.2210.0000.0000.0000.0000.0000.0610.0000.0000.0000.0000.0150.0000.0000.0000.0310.0000.0390.0000.0100.0000.0000.0000.0000.0450.0000.0390.0000.0000.0000.0000.000
estado_civil_SOLTERO0.0590.0210.0130.0150.7490.2230.2211.0000.0220.0220.0130.0000.0000.1430.0080.0080.0770.0250.0330.0140.0000.0000.0000.0060.0000.0000.0000.0180.0000.0000.0040.1370.0330.0380.0320.0270.0040.0000.000
estado_cliente_ACTIVO0.0000.0250.0050.0160.0310.0000.0000.0221.0000.9990.1160.5620.5620.3370.0270.0270.1080.0000.0230.0060.0270.0000.0000.0000.0110.0270.0000.0340.0000.0000.0000.4620.0380.0130.0550.0490.0000.0000.326
estado_cliente_PASIVO0.0000.0250.0050.0160.0310.0000.0000.0220.9991.0000.1160.5620.5620.3370.0270.0270.1080.0000.0230.0060.0270.0000.0000.0000.0110.0270.0000.0340.0000.0000.0000.4620.0380.0130.0550.0490.0000.0000.326
estado_credito0.0270.1050.0450.0370.0290.0300.0000.0130.1160.1161.0000.1820.1820.2280.0290.0290.2070.1120.0250.0000.0100.0000.0000.0000.0000.0930.0580.1300.0580.0210.0270.2340.4090.0000.2060.1660.0130.0960.378
falta_pago_N0.0450.0290.0000.0000.0000.0000.0000.0000.5620.5620.1821.0000.9990.2570.0000.0000.0450.0000.0280.0000.0000.0000.0180.0000.0000.0170.0210.0530.0130.0010.0000.3190.0540.0150.0710.0650.0000.0050.564
falta_pago_Y0.0450.0290.0000.0000.0000.0000.0000.0000.5620.5620.1820.9991.0000.2570.0000.0000.0450.0000.0280.0000.0000.0000.0180.0000.0000.0170.0210.0530.0130.0010.0000.3190.0540.0150.0710.0650.0000.0050.564
gastos_ult_12m-0.0210.0550.0110.0080.1750.0350.0610.1430.3370.3370.2280.2570.2571.0000.2560.2560.0290.1580.0280.0000.0000.0000.0450.0000.0000.0120.0000.0260.0000.0100.0000.877-0.0750.0600.1450.1760.0000.039-0.195
genero_F0.0290.0000.0060.0000.0000.0160.0000.0080.0270.0270.0290.0000.0000.2561.0001.0000.1840.1120.4410.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.1730.0700.0000.0280.0330.0000.0000.019
genero_M0.0290.0000.0060.0000.0000.0160.0000.0080.0270.0270.0290.0000.0000.2561.0001.0000.1840.1120.4410.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.1730.0700.0000.0280.0330.0000.0000.019
importe_solicitado0.0370.1150.1120.0740.0870.0400.0000.0770.1080.1080.2070.0450.0450.0290.1840.1841.0000.3520.0500.0220.0390.0200.0000.0250.0000.0000.0000.0390.0020.0050.058-0.0010.7330.0190.1930.1750.0140.0540.074
ingresos0.0080.1890.0000.1460.0420.0430.0000.0250.0000.0000.1120.0000.0000.1580.1120.1120.3521.0000.0370.0070.0300.0000.0210.0000.0090.0000.0000.0470.0450.0140.0320.128-0.2980.0380.1570.1170.0000.086-0.021
limite_credito_tc-0.003-0.0170.0280.0060.0650.0050.0150.0330.0230.0230.0250.0280.0280.0280.4410.4410.0500.0371.0000.0000.0300.0000.0000.0000.0240.0370.0000.0000.0290.0000.0000.0310.0300.0510.0100.0330.0000.013-0.002
nivel_educativo_DESCONOCIDO0.0200.0000.0080.0000.0000.0000.0000.0140.0060.0060.0000.0000.0000.0000.0000.0000.0220.0070.0001.0000.0900.0940.2100.2740.2460.0000.0060.0270.0370.0000.0000.0000.0000.0220.0000.0000.0080.0110.000
nivel_educativo_POSGRADO_COMPLETO0.0290.0290.0220.0020.0000.0000.0000.0000.0270.0270.0100.0000.0000.0000.0000.0000.0390.0300.0300.0901.0000.0460.1080.1410.1260.0110.0000.0200.0000.0000.0000.0270.0220.0000.0000.0000.0000.0000.000
nivel_educativo_POSGRADO_INCOMPLETO0.0180.0000.0000.0330.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0200.0000.0000.0940.0461.0000.1120.1470.1320.0000.0260.0000.0060.0000.0000.0000.0000.0160.0000.0000.0000.0080.000
nivel_educativo_SECUNDARIO_COMPLETO0.0000.0130.0000.0000.0000.0000.0310.0000.0000.0000.0000.0180.0180.0450.0150.0150.0000.0210.0000.2100.1080.1121.0000.3250.2930.0000.0000.0000.0000.0000.0140.0000.0220.0200.0250.0160.0060.0000.013
nivel_educativo_UNIVERSITARIO_COMPLETO0.0230.0490.0120.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0250.0000.0000.2740.1410.1470.3251.0000.3810.0200.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0200.000
nivel_educativo_UNIVERSITARIO_INCOMPLETO0.0310.0220.0000.0000.0030.0000.0390.0000.0110.0110.0000.0000.0000.0000.0000.0000.0000.0090.0240.2460.1260.1320.2930.3811.0000.0160.0000.0260.0000.0000.0000.0000.0000.0390.0160.0170.0000.0000.000
objetivo_credito_EDUCACIÓN0.0000.0590.0270.1690.0000.0000.0000.0000.0270.0270.0930.0170.0170.0120.0000.0000.0000.0000.0370.0000.0110.0000.0000.0200.0161.0000.2450.1680.2470.2450.2550.0000.0360.0000.0230.0160.0000.0000.028
objetivo_credito_INVERSIONES0.0000.0300.0080.0170.0090.0000.0100.0000.0000.0000.0580.0210.0210.0000.0000.0000.0000.0000.0000.0060.0000.0260.0000.0000.0000.2451.0000.1360.2010.1990.2080.0000.0170.0140.0580.0000.0000.0920.037
objetivo_credito_MEJORAS_HOGAR0.0170.0990.0130.1930.0000.0000.0000.0180.0340.0340.1300.0530.0530.0260.0000.0000.0390.0470.0000.0270.0200.0000.0000.0000.0260.1680.1361.0000.1370.1360.1420.0140.0420.0330.0280.0140.0000.0160.063
objetivo_credito_PAGO_DEUDAS0.0540.0150.0000.0220.0000.0000.0000.0000.0000.0000.0580.0130.0130.0000.0000.0000.0020.0450.0290.0370.0000.0060.0000.0060.0000.2470.2010.1371.0000.2010.2100.0260.0000.0320.0300.0040.0140.0920.000
objetivo_credito_PERSONAL0.0370.0170.0230.0000.0000.0000.0000.0000.0000.0000.0210.0010.0010.0100.0000.0000.0050.0140.0000.0000.0000.0000.0000.0000.0000.2450.1990.1360.2011.0000.2080.0400.0120.0430.0110.0170.0110.0000.017
objetivo_credito_SALUD0.0000.0000.0250.0490.0000.0000.0000.0040.0000.0000.0270.0000.0000.0000.0000.0000.0580.0320.0000.0000.0000.0000.0140.0000.0000.2550.2080.1420.2100.2081.0000.0000.0160.0000.0340.0360.0000.0000.000
operaciones_ult_12m-0.0380.0480.0070.0010.1670.0210.0450.1370.4620.4620.2340.3190.3190.8770.1730.173-0.0010.1280.0310.0000.0270.0000.0000.0000.0000.0000.0000.0140.0260.0400.0001.000-0.0820.0590.1340.1620.0000.045-0.223
pct_ingreso0.038-0.0130.427-0.0360.0500.0100.0000.0330.0380.0380.4090.0540.054-0.0750.0700.0700.733-0.2980.0300.0000.0220.0000.0220.0000.0000.0360.0170.0420.0000.0120.016-0.0821.0000.0010.0470.0340.0350.0370.087
personas_a_cargo-0.107-0.0000.0120.0100.0000.0230.0390.0380.0130.0130.0000.0150.0150.0600.0000.0000.0190.0380.0510.0220.0000.0160.0200.0000.0390.0000.0140.0330.0320.0430.0000.0590.0011.0000.0000.0000.0080.002-0.015
situacion_vivienda_ALQUILER0.0330.1990.0000.0000.0230.0060.0000.0320.0550.0550.2060.0710.0710.1450.0280.0280.1930.1570.0100.0000.0000.0000.0250.0000.0160.0230.0580.0280.0300.0110.0340.1340.0470.0001.0000.8480.0750.3470.149
situacion_vivienda_HIPOTECA0.0450.1910.0000.0260.0140.0070.0000.0270.0490.0490.1660.0650.0650.1760.0330.0330.1750.1170.0330.0000.0000.0000.0160.0000.0170.0160.0000.0140.0040.0170.0360.1620.0340.0000.8481.0000.0370.1830.150
situacion_vivienda_OTROS0.0000.0150.0000.0250.0110.0000.0000.0040.0000.0000.0130.0000.0000.0000.0000.0000.0140.0000.0000.0080.0000.0000.0060.0000.0000.0000.0000.0000.0140.0110.0000.0000.0350.0080.0750.0371.0000.0000.000
situacion_vivienda_PROPIA0.0190.0360.0000.0330.0000.0000.0000.0000.0000.0000.0960.0050.0050.0390.0000.0000.0540.0860.0130.0110.0000.0080.0000.0200.0000.0000.0920.0160.0920.0000.0000.0450.0370.0020.3470.1830.0001.0000.000
tasa_interes0.000-0.0640.0360.0100.0000.0340.0000.0000.3260.3260.3780.5640.564-0.1950.0190.0190.074-0.021-0.0020.0000.0000.0000.0130.0000.0000.0280.0370.0630.0000.0170.000-0.2230.087-0.0150.1490.1500.0000.0001.000

Missing values

2025-07-12T17:25:51.831994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-07-12T17:25:52.216610image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

edadimporte_solicitadoduracion_creditoantiguedad_empleadoingresospct_ingresotasa_interesestado_creditoantiguedad_clientegastos_ult_12mlimite_credito_tcoperaciones_ult_12mpersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDfalta_pago_Nfalta_pago_Yregla_duracion_pct_okestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOgenero_Fgenero_Mnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETO
025550031.096000.5712.87144.01291.08256.033.05.0FalseTrueFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalse
1243500048.0544000.5514.27154.01314.09095.026.01.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueTrueTrueFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseFalseFalse
2263500038.0771000.4512.42121.0816.04716.028.03.0TrueFalseFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseFalseTrue
3243500045.0789560.4411.11146.01330.034516.031.04.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseTrueTrueFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseFalseFalse
421160036.0100000.1614.74136.01350.022352.024.03.0FalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseFalseTrue
5223500046.0850000.4110.37136.01441.011656.032.02.0TrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseTrueFalse
6263500044.01081600.3218.39130.01311.08547.033.03.0TrueFalseFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseTrueFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueFalse
7233500042.01150000.307.90048.01570.02436.029.02.0TrueFalseFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueTrueFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseFalseTrueFalse
8233000037.05000000.0610.65037.01348.04234.027.04.0FalseTrueFalseFalseFalseFalseFalseTrueFalseFalseTrueFalseTrueFalseTrueFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseFalseFalse
9233500040.01200000.297.90036.01671.030367.027.04.0TrueFalseFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseTrueFalseFalseFalse
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